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Models/openai/image · text-to-image · image-editingPass-through

GPT Image 2.5 Flare

Generate images from text or revise them with up to 16 ordered reference images. Choose from eight aspect ratios and output sizes up to 4K.

Current MachGen support
Text to ImageImage Editing1K / 1080p / 2K / 4KUp to 16 input images
Starting at $0.066 / image
1280×544$0.066/image
1280×720$0.094/image
1920×816$0.087/image
1280×848$0.118/image
2048×880$0.093/image
1280×960$0.138/image
+16 more price tiers in the full pricebookLive public pricebookSee full pricebook
Overview

GPT Image 2.5 Flare

Generate images from text or revise them with up to 16 ordered reference images. Choose from eight aspect ratios and output sizes up to 4K.

GPT Image 2.5 Flare API on MachGen. Compare supported generation modes, examples, and current pricing from the live pricebook.

Model guide

Why choose GPT Image 2.5 Flare

Key strengths

  • Fast image generation for everyday creative work.
  • Generate from text or edit with up to 16 ordered reference images.

Good fit for

  • Visual drafts, social graphics, and image revisions.
Supported on MachGen

Inputs and output settings

This table reflects the model routes and controls currently exposed by MachGen.

ModeRequired inputAvailable settings
Text to ImageText promptExact output grid: 1:1: 1024p 1280x1280, 2048p 2048x2048; 16:9: 1024p 1280x720, 1080p 1920x1088, 2048p 2048x1152, 4096p 3840x2160; 21:9: 1024p 1280x544, 1080p 1920x816, 2048p 2048x880, 4096p 3840x1648; 9:16: 1024p 720x1280, 1080p 1088x1920, 2048p 1152x2048, 4096p 2160x3840; 4:3: 1024p 1280x960, 2048p 2048x1536; 3:4: 1024p 960x1280, 2048p 1536x2048; 3:2: 1024p 1280x848, 2048p 2048x1360; 2:3: 1024p 848x1280, 2048p 1360x2048
Image EditingText prompt and up to 16 source imagesExact output grid: 1:1: 1024p 1280x1280, 2048p 2048x2048; 16:9: 1024p 1280x720, 1080p 1920x1088, 2048p 2048x1152, 4096p 3840x2160; 21:9: 1024p 1280x544, 1080p 1920x816, 2048p 2048x880, 4096p 3840x1648; 9:16: 1024p 720x1280, 1080p 1088x1920, 2048p 1152x2048, 4096p 2160x3840; 4:3: 1024p 1280x960, 2048p 2048x1536; 3:4: 1024p 960x1280, 2048p 1536x2048; 3:2: 1024p 1280x848, 2048p 2048x1360; 2:3: 1024p 848x1280, 2048p 1360x2048
Workflow

Using GPT Image 2.5 Flare

  1. Choose a supported generation mode in Playground.
  2. Add the required prompt and source or reference assets.
  3. Select output settings from the controls shown for that mode.
  4. Generate, then inspect the returned asset before reusing the settings through the API.

Practical guidance

  • Describe the subject, action or composition, environment, and visual direction in a clear order.
  • For image editing, state what should change and what should remain unchanged.
Best results

How to get better GPT Image 2.5 Flare results

  • Specify the subject, composition, and visual style in the prompt.
  • For edits, describe the change and what should stay the same.
Limits

Limits and availability

  • MachGen admits only the modes and settings listed above for this catalog model.
  • Source assets must finish uploading before a request can be submitted.
  • Generated results can vary between requests, including when the same prompt and settings are reused.
  • GPT Image 2.5 Flare is pass-through. MachGen sends the request through its upstream provider integration and returns the generated asset.
Learn more

Learn more

For model background, technical details, and architecture, see the official GPT Image 2.5 Flare documentation.

Try this model in the MachGen Playground.

Official documentation may describe capabilities or parameters that are not currently exposed by MachGen. Use the Inputs and output settings section above as the source of truth for this page.

Pricing

GPT Image 2.5 Flare pricing

See Pricing for currently published MachGen rates. When available, the Playground estimate reflects the selected task and output settings.

On MachGen

GPT Image 2.5 Flare on MachGen

Deployment: Pass-through. GPT Image 2.5 Flare is pass-through. MachGen sends the request through its upstream provider integration and returns the generated asset.

The Playground and API sections on this page list the inputs and output settings exposed for this model.